Mercurial > repos > bgruening > flexynesis
diff flexynesis.xml @ 6:33816f44fc7d draft default tip
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/flexynesis commit 6b520305ec30e6dc37eba92c67a5368cea0fc5ad
| author | bgruening |
|---|---|
| date | Wed, 23 Jul 2025 07:49:41 +0000 |
| parents | 466b593fd87e |
| children |
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--- a/flexynesis.xml Fri Jul 04 14:57:40 2025 +0000 +++ b/flexynesis.xml Wed Jul 23 07:49:41 2025 +0000 @@ -7,15 +7,18 @@ <expand macro="requirements"/> <required_files> <include path="flexynesis_plot.py" /> + <include path="flexynesis_utils.py" /> + <include path="convert.py" /> + <include path="index_to_name.py" /> </required_files> <command detect_errors="exit_code"><![CDATA[ @CHECK_NON_COMMERCIAL_USE@ mkdir -p input/test input/train output && ln -s '$train_clin' input/train/clin.tabular && - python $__tool_directory__/convert.py input/train/clin.tabular input/train/clin.csv && + python '$__tool_directory__/convert.py' input/train/clin.tabular input/train/clin.csv && ln -s '$test_clin' input/test/clin.tabular && - python $__tool_directory__/convert.py input/test/clin.tabular input/test/clin.csv && + python '$__tool_directory__/convert.py' input/test/clin.tabular input/test/clin.csv && #if str($assay_main) != '': #set $name = str($assay_main.replace(" ", "_")) @@ -46,54 +49,61 @@ #if str($element.train_omics) != 'None' and str($element.test_omics) != 'None': #if str($element.assay) != '': #set $i = str($element.assay.replace(" ", "_")) - #end if - ln -s '${element.train_omics}' input/train/omics_${i}.tabular && - python '$__tool_directory__/convert.py' input/train/omics_${i}.tabular input/train/omics_${i}.csv && + ln -s '${element.train_omics}' input/train/${i}.tabular && + python '$__tool_directory__/convert.py' input/train/${i}.tabular input/train/${i}.csv && - ln -s '${element.test_omics}' input/test/omics_${i}.tabular && - python '$__tool_directory__/convert.py' input/test/omics_${i}.tabular input/test/omics_${i}.csv && + ln -s '${element.test_omics}' input/test/${i}.tabular && + python '$__tool_directory__/convert.py' input/test/${i}.tabular input/test/${i}.csv && - $data_names.append("omics_" + str($i)) - #if str($training_type.model) == 'cm_train': - #if str($element.layer) == 'input': - $input_layers.append("omics_" + str($i)) - #else - $output_layers.append("omics_" + str($i)) + $data_names.append(str($i)) + #if str($training_type.model) == 'cm_train': + #if str($element.layer) == 'input': + $input_layers.append(str($i)) + #else + $output_layers.append(str($i)) + #end if + #end if + #else + ln -s '${element.train_omics}' input/train/omics_${i}.tabular && + python '$__tool_directory__/convert.py' input/train/omics_${i}.tabular input/train/omics_${i}.csv && + + ln -s '${element.test_omics}' input/test/omics_${i}.tabular && + python '$__tool_directory__/convert.py' input/test/omics_${i}.tabular input/test/omics_${i}.csv && + + $data_names.append("omics_" + str($i)) + #if str($training_type.model) == 'cm_train': + #if str($element.layer) == 'input': + $input_layers.append("omics_" + str($i)) + #else + $output_layers.append("omics_" + str($i)) + #end if #end if #end if #end if #end for - ## set target variables #if str($training_type.model) == 's_train': - #if len($targets) > 0: - target_variables="" && - #for $i, $element in enumerate($targets) - target_name=`$__tool_directory__/index_to_name.py input/train/clin.csv $element.target_variables` && - #if $i == 0: - target_variables="\$target_name" && - #else: - target_variables="\$target_variables,\$target_name" && - #end if - #end for - echo "Target variables: \$target_variables" && + ## set target variables + #if str($target_variables) != 'None': + targets=`'$__tool_directory__/index_to_name.py' input/train/clin.csv $target_variables` && + echo "Target variables: \$targets" && #end if ## set survival variables #if str($surv_event_var) != 'None' and str($surv_time_var) != 'None': - surv_event_var=`$__tool_directory__/index_to_name.py input/train/clin.csv $surv_event_var` && - echo "Survival event variable: \$surv_event_var" && - surv_time_var=`$__tool_directory__/index_to_name.py input/train/clin.csv $surv_time_var` && - echo "Survival time variable: \$surv_time_var" && + survival_event=`'$__tool_directory__/index_to_name.py' input/train/clin.csv $surv_event_var` && + ## check if survival variable is numerical + echo "Survival event variable: \$survival_event" && + python '$__tool_directory__/flexynesis_utils.py' --util validate_survival --clin input/train/clin.csv --clin_variable \$survival_event && + survival_time=`$__tool_directory__/index_to_name.py input/train/clin.csv $surv_time_var` && + echo "Survival time variable: \$survival_time" && #end if - ## set target value for plots - #if str($surv_event_var) != 'None' and str($surv_time_var) != 'None' and len($targets) > 0: - target_value="\$target_variables,\$surv_event_var" && - echo "Target value for plots: \$target_value" && - #else if str($surv_event_var) == 'None' and str($surv_time_var) == 'None' and len($targets) > 0: - target_value="\$target_variables" && - echo "Target value for plots: \$target_value" && - #else if str($surv_event_var) != 'None' and str($surv_time_var) != 'None' and len($targets) == 0: - target_value="\$surv_event_var" && - echo "Target value for plots: \$target_value" && + ## set clinical variables for Cox model + #if str($plot.plot_cox_conditional.plot_cox) == 'yes': + #if str($plot.plot_cox_conditional.clinical_variables) != 'None': + covars=`'$__tool_directory__/index_to_name.py' input/train/clin.csv $plot.plot_cox_conditional.clinical_variables` && + ## check if covariates is numerical + echo "Clinical variables for Cox model: \$covars" && + python '$__tool_directory__/flexynesis_utils.py' --util validate_covariate --clin input/train/clin.csv --clin_variable \$covars && + #end if #end if #end if @@ -107,12 +117,12 @@ --string_node_name $string_node_name #end if #if str($training_type.model) == 's_train': - #if len($targets) > 0: - --target_variables \$target_variables + #if str($target_variables) != 'None': + --target_variables \$targets #end if #if str($surv_event_var) != 'None' and str($surv_time_var) != 'None': - --surv_event_var \$surv_event_var - --surv_time_var \$surv_time_var + --surv_event_var \$survival_event + --surv_time_var \$survival_time #end if #end if #if str($training_type.model) == 'cm_train': @@ -142,143 +152,151 @@ && for file in output/*.csv; do if [ -f "\$file" ]; then basename="\${file%.csv}"; - python $__tool_directory__/convert.py "\$file" "\${basename}.tabular"; + python '$__tool_directory__/convert.py' "\$file" "\${basename}.tabular"; echo "Converted \$file to \${basename}.tabular"; fi done - #if str($plot.plot_embeddings_conditional.plot_embeddings) == 'yes': - && python $__tool_directory__/flexynesis_plot.py - --plot_type dimred - --embeddings output/job.embeddings_test.tabular + #if str($training_type.model) == 's_train': + #if str($plot.plot_embeddings_conditional.plot_embeddings) == 'yes': + && python '$__tool_directory__/flexynesis_plot.py' + --plot_type dimred + --embeddings output/job.embeddings_test.tabular + --labels output/job.predicted_labels.tabular + --method $plot.plot_embeddings_conditional.method + #if str($training_type.model) == 's_train': + #if str($target_variables) != 'None': + --target_value \$targets + #end if + #end if + --output_dir plots + --format $plot.plot_embeddings_conditional.format + --dpi $plot.plot_embeddings_conditional.dpi + #end if + #if str($plot.plot_km_conditional.plot_km) == 'yes': + #if str($surv_event_var) == '' or str($surv_time_var) == '': + && echo "Survival event and time variables must be specified for Kaplan-Meier plots." + && exit 1 + #else + && python '$__tool_directory__/flexynesis_plot.py' + --plot_type kaplan_meier + --labels output/job.predicted_labels.tabular + --survival_data input/test/clin.csv + --surv_event_var \$survival_event + --surv_time_var \$survival_time + --output_dir plots + --format $plot.plot_km_conditional.format + --dpi $plot.plot_km_conditional.dpi + #end if + #end if + #if str($plot.plot_cox_conditional.plot_cox) == 'yes': + #if str($surv_event_var) == '' or str($surv_time_var) == '': + && echo "Survival event and time variables must be specified for cox plots." + && exit 1 + #else + && python '$__tool_directory__/flexynesis_plot.py' + --plot_type cox + #if str($feature_importance_method) == 'GradientShap': + --important_features output/job.feature_importance.GradientShap.tabular + #else if str($feature_importance_method) == 'IntegratedGradients': + --important_features output/job.feature_importance.IntegratedGradients.tabular + #else + --important_features output/job.feature_importance.IntegratedGradients.tabular + #end if + --clinical_train input/train/clin.csv + --clinical_test input/test/clin.csv + #if str($plot.plot_cox_conditional.omics_name) != '': + #set $omics_name = str($plot.plot_cox_conditional.omics_name.replace(" ", "_")) + --omics_train input/train/${omics_name}.csv + --omics_test input/test/${omics_name}.csv + --layer ${omics_name} + #else + --omics_train input/train/${data_names}.csv + --omics_test input/test/${data_names}.csv + --layer ${data_names} + #end if + --surv_time_var \$survival_time + --surv_event_var \$survival_event + #if str($plot.plot_cox_conditional.clinical_variables) != 'None': + --clinical_variables \$covars + #end if + --top_features $plot.plot_cox_conditional.top_features + #if str($plot.plot_cox_conditional.crossval_conditional.crossval) == 'yes': + --crossval + #end if + #if str($plot.plot_cox_conditional.crossval_conditional.crossval) == 'yes': + --n_splits $plot.plot_cox_conditional.crossval_conditional.n_splits + #end if + --random_state 42 + --output_dir plots + --format $plot.plot_cox_conditional.format + --dpi $plot.plot_cox_conditional.dpi + #end if + #end if + #if str($plot.plot_scatter_conditional.plot_scatter) == 'yes': + && python '$__tool_directory__/flexynesis_plot.py' + --plot_type scatter --labels output/job.predicted_labels.tabular - --method $plot.plot_embeddings_conditional.method #if str($training_type.model) == 's_train': - #if len($targets) > 0 or (str($surv_event_var) != 'None' and str($surv_time_var) != 'None'): - --target_value \$target_value + #if str($target_variables) != 'None': + --target_value \$targets #end if #end if --output_dir plots - --format $plot.plot_embeddings_conditional.format - --dpi $plot.plot_embeddings_conditional.dpi - #end if - #if str($plot.plot_km_conditional.plot_km) == 'yes': - #if str($surv_event_var) == '' or str($surv_time_var) == '': - && echo "Survival event and time variables must be specified for Kaplan-Meier plots." - && exit 1 - #else - && python $__tool_directory__/flexynesis_plot.py - --plot_type kaplan_meier - --labels output/job.predicted_labels.tabular - --survival_data input/test/clin.csv - --surv_event_var \$surv_event_var - --surv_time_var \$surv_time_var - --event_value $plot.plot_km_conditional.event_value - --output_dir plots - --format $plot.plot_km_conditional.format - --dpi $plot.plot_km_conditional.dpi + --format $plot.plot_scatter_conditional.format + --dpi $plot.plot_scatter_conditional.dpi #end if - #end if - #if str($plot.plot_cox_conditional.plot_cox) == 'yes': - #if str($surv_event_var) == '' or str($surv_time_var) == '': - && echo "Survival event and time variables must be specified for cox plots." - && exit 1 - #else - && python $__tool_directory__/flexynesis_plot.py - --plot_type cox - --model output/job.final_model.pth - --clinical_train input/train/clin.csv - --clinical_test input/test/clin.csv - #if str($plot.plot_cox_conditional.omics_name) != '': - #set $name = str($plot.plot_cox_conditional.omics_name.replace(" ", "_")) - --omics_train input/train/${name}.csv - --omics_test input/test/${name}.csv - #else - --omics_train input/train/main.csv - --omics_test input/test/main.csv + #if str($plot.plot_concordance_conditional.plot_concordance) == 'yes': + && python '$__tool_directory__/flexynesis_plot.py' + --plot_type concordance_heatmap + --labels output/job.predicted_labels.tabular + #if str($training_type.model) == 's_train': + #if str($target_variables) != 'None': + --target_value \$targets + #end if #end if - --surv_time_var \$surv_time_var - --surv_event_var \$surv_event_var - #if str($plot.plot_cox_conditional.clinical_variables) != '': - --clinical_variables $str($plot.plot_cox_conditional.clinical_variables) - #end if - --top_features $plot.plot_cox_conditional.top_features - --event_value $plot.plot_cox_conditional.event_value - #if str($plot.plot_cox_conditional.crossval_conditional.crossval) == 'yes': - --crossval - #end if - #if str($plot.plot_cox_conditional.crossval_conditional.crossval) == 'yes': - --n_splits $plot.plot_cox_conditional.crossval_conditional.n_splits - #end if - --random_state 42 --output_dir plots - --format $plot.plot_cox_conditional.format - --dpi $plot.plot_cox_conditional.dpi + --format $plot.plot_concordance_conditional.format + --dpi $plot.plot_concordance_conditional.dpi #end if - #end if - #if str($plot.plot_scatter_conditional.plot_scatter) == 'yes': - && python $__tool_directory__/flexynesis_plot.py - --plot_type scatter - --labels output/job.predicted_labels.tabular - #if str($training_type.model) == 's_train': - #if len($targets) > 0 or (str($surv_event_var) != 'None' and str($surv_time_var) != 'None'): - --target_value \$target_value - #end if - #end if - --output_dir plots - --format $plot.plot_scatter_conditional.format - --dpi $plot.plot_scatter_conditional.dpi - #end if - #if str($plot.plot_concordance_conditional.plot_concordance) == 'yes': - && python $__tool_directory__/flexynesis_plot.py - --plot_type concordance_heatmap - --labels output/job.predicted_labels.tabular - #if str($training_type.model) == 's_train': - #if len($targets) > 0 or (str($surv_event_var) != 'None' and str($surv_time_var) != 'None'): - --target_value \$target_value + #if str($plot.plot_pr_curves_conditional.plot_pr_curves) == 'yes': + && python '$__tool_directory__/flexynesis_plot.py' + --plot_type pr_curve + --labels output/job.predicted_labels.tabular + #if str($training_type.model) == 's_train': + #if str($target_variables) != 'None': + --target_value \$targets + #end if #end if - #end if - --output_dir plots - --format $plot.plot_concordance_conditional.format - --dpi $plot.plot_concordance_conditional.dpi - #end if - #if str($plot.plot_pr_curves_conditional.plot_pr_curves) == 'yes': - && python $__tool_directory__/flexynesis_plot.py - --plot_type pr_curve - --labels output/job.predicted_labels.tabular - #if str($training_type.model) == 's_train': - #if len($targets) > 0 or (str($surv_event_var) != 'None' and str($surv_time_var) != 'None'): - --target_value \$target_value + --output_dir plots + --format $plot.plot_pr_curves_conditional.format + --dpi $plot.plot_pr_curves_conditional.dpi + #end if + #if str($plot.plot_roc_curves_conditional.plot_roc_curves) == 'yes': + && python '$__tool_directory__/flexynesis_plot.py' + --plot_type roc_curve + --labels output/job.predicted_labels.tabular + #if str($training_type.model) == 's_train': + #if str($target_variables) != 'None': + --target_value \$targets + #end if #end if - #end if - --output_dir plots - --format $plot.plot_pr_curves_conditional.format - --dpi $plot.plot_pr_curves_conditional.dpi - #end if - #if str($plot.plot_roc_curves_conditional.plot_roc_curves) == 'yes': - && python $__tool_directory__/flexynesis_plot.py - --plot_type roc_curve - --labels output/job.predicted_labels.tabular - #if str($training_type.model) == 's_train': - #if len($targets) > 0 or (str($surv_event_var) != 'None' and str($surv_time_var) != 'None'): - --target_value \$target_value + --output_dir plots + --format $plot.plot_roc_curves_conditional.format + --dpi $plot.plot_roc_curves_conditional.dpi + #end if + #if str($plot.plot_boxplot_conditional.plot_boxplot) == 'yes': + && python '$__tool_directory__/flexynesis_plot.py' + --plot_type box_plot + --labels output/job.predicted_labels.tabular + #if str($training_type.model) == 's_train': + #if str($target_variables) != 'None': + --target_value \$targets + #end if #end if - #end if - --output_dir plots - --format $plot.plot_roc_curves_conditional.format - --dpi $plot.plot_roc_curves_conditional.dpi - #end if - #if str($plot.plot_boxplot_conditional.plot_boxplot) == 'yes': - && python $__tool_directory__/flexynesis_plot.py - --plot_type box_plot - --labels output/job.predicted_labels.tabular - #if str($training_type.model) == 's_train': - #if len($targets) > 0 or (str($surv_event_var) != 'None' and str($surv_time_var) != 'None'): - --target_value \$target_value - #end if - #end if - --output_dir plots - --format $plot.plot_boxplot_conditional.format - --dpi $plot.plot_boxplot_conditional.dpi + --output_dir plots + --format $plot.plot_boxplot_conditional.format + --dpi $plot.plot_boxplot_conditional.dpi + #end if #end if ]]></command> <inputs> @@ -328,12 +346,119 @@ <when value="RandomSurvivalForest"/> <when value="XGBoost"/> </conditional> - <repeat name="targets" min="0" title="Target variables"> - <param argument="--target_variables" type="data_column" data_ref="train_clin" optional="false" label="Column name in the train clinical data to use for predictions, multiple targets are allowed"/> - </repeat> + <param argument="--target_variables" type="data_column" data_ref="train_clin" optional="true" multiple="true" label="Column name in the train clinical data to use for predictions, multiple targets are allowed"/> <param argument="--surv_event_var" type="data_column" data_ref="train_clin" optional="true" label="Column name in the train clinical data to use as survival event"/> <param argument="--surv_time_var" type="data_column" data_ref="train_clin" optional="true" label="Column name in the train clinical data to use as survival time"/> <expand macro="advanced"/> + <section name="plot" title="Visualization"> + <conditional name="plot_embeddings_conditional"> + <param name="plot_embeddings" type="select" label="Generate embeddings plot?" help="Generate PCA or UMAP plot of the test dataset"> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="no"> + </when> + <when value="yes"> + <param name="method" type="select" label="Transformation method"> + <option value="pca" selected="true">PCA</option> + <option value="umap">UMAP</option> + </param> + <expand macro="plots_common_param"/> + </when> + </conditional> + <conditional name="plot_km_conditional"> + <param name="plot_km" type="select" label="Generate kaplan meier curves plot?" help="Generate KM curves plot of risk subtype based on predicted events probabilities"> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="no"> + </when> + <when value="yes"> + <expand macro="plots_common_param"/> + </when> + </conditional> + <conditional name="plot_cox_conditional"> + <param name="plot_cox" type="select" label="Generate hazard ratio plot?" help="Performs Cox regression on data based on top features and selected clinical covariates."> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="no"> + </when> + <when value="yes"> + <param name="omics_name" type="text" label="Omics layer to use for cox input" optional="true" help="If not specified, the first omics layer will be used."> + <expand macro="sanitizer_printable"/> + </param> + <param argument="--clinical_variables" type="data_column" data_ref="train_clin" optional="true" multiple="true" label="Columns in the train clinical data to use as clinical covariates and include in the Cox model (e.g SEX, AGE, ...), multiple covariates are allowed"/> + <param argument="--top_features" type="integer" min="1" value="20" label="Number of top important features to include in Cox model"/> + <conditional name="crossval_conditional"> + <param name="crossval" type="select" label="Performs K-fold cross-validation?"> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="yes"> + <param name="n_splits" type="integer" min="2" value="5" label="Number of folds for cross-validation"/> + </when> + <when value="no"/> + </conditional> + <expand macro="plots_common_param"/> + </when> + </conditional> + <conditional name="plot_scatter_conditional"> + <param name="plot_scatter" type="select" label="Generate scatter plot?" help="Generates a scatter plot of numeric true and predicted labels for all available targets."> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="no"> + </when> + <when value="yes"> + <expand macro="plots_common_param"/> + </when> + </conditional> + <conditional name="plot_concordance_conditional"> + <param name="plot_concordance" type="select" label="Generate concordance heatmap plot?" help="Generates a plot showing the concordance between true and predicted labels for all targets."> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="no"> + </when> + <when value="yes"> + <expand macro="plots_common_param"/> + </when> + </conditional> + <conditional name="plot_pr_curves_conditional"> + <param name="plot_pr_curves" type="select" label="Generate precision-recall curves plot?" help="Generates precision-recall curves for all available targets."> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="no"> + </when> + <when value="yes"> + <expand macro="plots_common_param"/> + </when> + </conditional> + <conditional name="plot_roc_curves_conditional"> + <param name="plot_roc_curves" type="select" label="Generate ROC curves plot?" help="Generates ROC curves for all available targets."> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="no"> + </when> + <when value="yes"> + <expand macro="plots_common_param"/> + </when> + </conditional> + <conditional name="plot_boxplot_conditional"> + <param name="plot_boxplot" type="select" label="Generate boxplot?" help="Generates a boxplot for all available targets."> + <option value="yes">Yes</option> + <option value="no" selected="true">No</option> + </param> + <when value="no"> + </when> + <when value="yes"> + <expand macro="plots_common_param"/> + </when> + </conditional> + </section> </when> <when value="us_train"> <expand macro="main_inputs"/> @@ -364,131 +489,14 @@ <expand macro="advanced"/> </when> </conditional> - <section name="plot" title="Visualization"> - <conditional name="plot_embeddings_conditional"> - <param name="plot_embeddings" type="select" label="Generate embeddings plot?" help="Generate PCA or UMAP plot of the test dataset"> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="no"> - </when> - <when value="yes"> - <param name="method" type="select" label="Transformation method"> - <option value="pca" selected="true">PCA</option> - <option value="umap">UMAP</option> - </param> - <expand macro="plots_common_param"/> - </when> - </conditional> - <conditional name="plot_km_conditional"> - <param name="plot_km" type="select" label="Generate kaplan meier curves plot?" help="Generate KM curves plot of risk subtype based on predicted events probabilities"> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="no"> - </when> - <when value="yes"> - <param name="event_value" type="text" label="Event value" optional="false" help="The value in the event column that indicates an event (e.g. death) has occurred."> - <expand macro="sanitizer_printable"/> - </param> - <expand macro="plots_common_param"/> - </when> - </conditional> - <conditional name="plot_cox_conditional"> - <param name="plot_cox" type="select" label="Generate hazard ratio plot?" help="Performs Cox regression on data based on top features and selected clinical covariates."> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="no"> - </when> - <when value="yes"> - <param name="omics_name" type="text" label="Omics layer to use for cox input" optional="false" help="If not specified, the first omics layer will be used."> - <expand macro="sanitizer_printable"/> - </param> - <param name="clinical_variables" type="text" label="Clinical covariates" optional="true" help="Comma-separated list of clinical covariates to include in the Cox model (e.g SEX, AGE, ...)."> - <expand macro="sanitizer_printable"/> - </param> - <param argument="--top_features" type="integer" min="1" value="20" label="Number of top important features to include in Cox model"/> - <param name="event_value" type="text" label="Event value" optional="false" help="The value in the event column that indicates an event (e.g. death) has occurred."> - <expand macro="sanitizer_printable"/> - </param> - <conditional name="crossval_conditional"> - <param name="crossval" type="select" label="Performs K-fold cross-validation?"> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="yes"> - <param name="n_splits" type="integer" min="2" value="5" label="Number of folds for cross-validation"/> - </when> - <when value="no"/> - </conditional> - <expand macro="plots_common_param"/> - </when> - </conditional> - <conditional name="plot_scatter_conditional"> - <param name="plot_scatter" type="select" label="Generate scatter plot?" help="Generates a scatter plot of numeric true and predicted labels for all available targets."> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="no"> - </when> - <when value="yes"> - <expand macro="plots_common_param"/> - </when> - </conditional> - <conditional name="plot_concordance_conditional"> - <param name="plot_concordance" type="select" label="Generate concordance heatmap plot?" help="Generates a plot showing the concordance between true and predicted labels for all targets."> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="no"> - </when> - <when value="yes"> - <expand macro="plots_common_param"/> - </when> - </conditional> - <conditional name="plot_pr_curves_conditional"> - <param name="plot_pr_curves" type="select" label="Generate precision-recall curves plot?" help="Generates precision-recall curves for all available targets."> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="no"> - </when> - <when value="yes"> - <expand macro="plots_common_param"/> - </when> - </conditional> - <conditional name="plot_roc_curves_conditional"> - <param name="plot_roc_curves" type="select" label="Generate ROC curves plot?" help="Generates ROC curves for all available targets."> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="no"> - </when> - <when value="yes"> - <expand macro="plots_common_param"/> - </when> - </conditional> - <conditional name="plot_boxplot_conditional"> - <param name="plot_boxplot" type="select" label="Generate boxplot?" help="Generates a boxplot for all available targets."> - <option value="yes">Yes</option> - <option value="no" selected="true">No</option> - </param> - <when value="no"> - </when> - <when value="yes"> - <expand macro="plots_common_param"/> - </when> - </conditional> - </section> </inputs> <outputs> <collection name="results" type="list" label="${tool.name} on ${on_string}: results"> <discover_datasets pattern="(?P<name>.+)\.tabular$" format="tabular" directory="output"/> </collection> - <collection name="plots" type="list" label="${tool.name} on ${on_string}: embeddings plots"> + <collection name="plots" type="list" label="${tool.name} on ${on_string}: plots"> <discover_datasets pattern="__name_and_ext__" directory="plots"/> - <filter>plot['plot_embeddings_conditional']['plot_embeddings'] == 'yes' or plot['plot_km_conditional']['plot_km'] == 'yes' or plot['plot_cox_conditional']['plot_cox'] == 'yes' or plot['plot_scatter_conditional']['plot_scatter'] == 'yes' or plot['plot_concordance_conditional']['plot_concordance'] == 'yes' or plot['plot_pr_curves_conditional']['plot_pr_curves'] == 'yes' or plot['plot_roc_curves_conditional']['plot_roc_curves'] == 'yes' or plot['plot_boxplot_conditional']['plot_boxplot'] == 'yes'</filter> + <filter>training_type['model'] == 's_train' and (training_type['plot']['plot_embeddings_conditional']['plot_embeddings'] == 'yes' or training_type['plot']['plot_km_conditional']['plot_km'] == 'yes' or training_type['plot']['plot_cox_conditional']['plot_cox'] == 'yes' or training_type['plot']['plot_scatter_conditional']['plot_scatter'] == 'yes' or training_type['plot']['plot_concordance_conditional']['plot_concordance'] == 'yes' or training_type['plot']['plot_pr_curves_conditional']['plot_pr_curves'] == 'yes' or training_type['plot']['plot_roc_curves_conditional']['plot_roc_curves'] == 'yes' or training_type['plot']['plot_boxplot_conditional']['plot_boxplot'] == 'yes')</filter> </collection> </outputs> <tests> @@ -510,9 +518,7 @@ <conditional name="model_class"> <param name="model_class" value="DirectPred"/> </conditional> - <repeat name="targets"> - <param name="target_variables" value="3"/> - </repeat> + <param name="target_variables" value="3"/> <section name="advanced"> <param name="hpo_iter" value="1"/> </section> @@ -547,7 +553,7 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_foo"> + <element name="job.feature_logs.foo"> <assert_contents> <has_n_lines n="25"/> </assert_contents> @@ -580,9 +586,7 @@ <conditional name="model_class"> <param name="model_class" value="DirectPred"/> </conditional> - <repeat name="targets"> - <param name="target_variables" value="3"/> - </repeat> + <param name="target_variables" value="3"/> <section name="advanced"> <param name="hpo_iter" value="1"/> </section> @@ -650,9 +654,7 @@ <conditional name="model_class"> <param name="model_class" value="DirectPred"/> </conditional> - <repeat name="targets"> - <param name="target_variables" value="4"/> - </repeat> + <param name="target_variables" value="4"/> <section name="advanced"> <param name="hpo_iter" value="1"/> </section> @@ -687,7 +689,7 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_foo"> + <element name="job.feature_logs.foo"> <assert_contents> <has_n_lines n="25"/> </assert_contents> @@ -743,7 +745,7 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_foo"> + <element name="job.feature_logs.foo"> <assert_contents> <has_n_lines n="25"/> </assert_contents> @@ -788,17 +790,17 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_foo"> + <element name="job.feature_logs.foo"> <assert_contents> <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.test_decoded.omics_foo"> + <element name="job.test_decoded.foo"> <assert_contents> <has_n_lines n="23"/> </assert_contents> </element> - <element name="job.train_decoded.omics_foo"> + <element name="job.train_decoded.foo"> <assert_contents> <has_n_lines n="23"/> </assert_contents> @@ -826,9 +828,7 @@ <param name="string_organism" value="9606"/> <param name="string_node_name" value="gene_name"/> </conditional> - <repeat name="targets"> - <param name="target_variables" value="3"/> - </repeat> + <param name="target_variables" value="3"/> <section name="advanced"> <param name="hpo_iter" value="1"/> </section> @@ -863,7 +863,7 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_foo"> + <element name="job.feature_logs.foo"> <assert_contents> <has_n_lines n="25"/> </assert_contents> @@ -919,7 +919,7 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_f_oo"> + <element name="job.feature_logs.f_oo"> <assert_contents> <has_n_lines n="25"/> </assert_contents> @@ -944,9 +944,7 @@ <conditional name="model_class"> <param name="model_class" value="XGBoost"/> </conditional> - <repeat name="targets"> - <param name="target_variables" value="3"/> - </repeat> + <param name="target_variables" value="3"/> <section name="advanced"> <param name="hpo_iter" value="1"/> </section> @@ -979,9 +977,7 @@ <conditional name="model_class"> <param name="model_class" value="DirectPred"/> </conditional> - <repeat name="targets"> - <param name="target_variables" value="3"/> - </repeat> + <param name="target_variables" value="3"/> <section name="advanced"> <param name="hpo_iter" value="1"/> <param name="feature_importance_method" value="IntegratedGradients"/> @@ -1010,7 +1006,7 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_foo"> + <element name="job.feature_logs.foo"> <assert_contents> <has_n_lines n="25"/> </assert_contents> @@ -1048,21 +1044,19 @@ <conditional name="model_class"> <param name="model_class" value="DirectPred"/> </conditional> - <repeat name="targets"> - <param name="target_variables" value="3"/> - </repeat> + <param name="target_variables" value="3"/> <section name="advanced"> <param name="hpo_iter" value="1"/> </section> + <section name="plot"> + <conditional name="plot_embeddings_conditional"> + <param name="plot_embeddings" value="yes"/> + <param name="method" value="pca"/> + <param name="format" value="jpg"/> + <param name="dpi" value="300"/> + </conditional> + </section> </conditional> - <section name="plot"> - <conditional name="plot_embeddings_conditional"> - <param name="plot_embeddings" value="yes"/> - <param name="method" value="pca"/> - <param name="format" value="jpg"/> - <param name="dpi" value="300"/> - </conditional> - </section> <output_collection name="results" type="list"> <element name="job.embeddings_test"> <assert_contents> @@ -1093,7 +1087,7 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_foo"> + <element name="job.feature_logs.foo"> <assert_contents> <has_n_lines n="25"/> </assert_contents> @@ -1137,7 +1131,6 @@ <section name="plot"> <conditional name="plot_km_conditional"> <param name="plot_km" value="yes"/> - <param name="event_value" value="1:DECEASED"/> <param name="format" value="jpg"/> <param name="dpi" value="300"/> </conditional> @@ -1161,16 +1154,15 @@ <conditional name="plot_cox_conditional"> <param name="plot_cox" value="yes"/> <param name="omics_name" value="bar"/> - <param name="clinical_variables" value="Crizotinib, Erlotinib"/> + <param name="clinical_variables" value="2,3"/> <param name="top_features" value="10"/> - <param name="event_value" value="1:DECEASED"/> <param name="format" value="jpg"/> <param name="dpi" value="300"/> </conditional> </section> </expand> <output_collection name="plots" type="list"> - <element name="job.final_model_cox_hazard_ratios"> + <element name="job.feature_importance.IntegratedGradients_cox_hazard_ratios"> <assert_contents> <has_image_center_of_mass center_of_mass="972,737" eps="20"/> <has_image_channels channels="3"/> @@ -1216,24 +1208,17 @@ <output_collection name="plots" type="list"> <element name="job.predicted_labels_concordance_Erlotinib"> <assert_contents> - <has_image_center_of_mass center_of_mass="1547,1620" eps="30"/> + <has_image_center_of_mass center_of_mass="1547,1590" eps="30"/> <has_image_channels channels="3"/> - <has_image_height height="3060" delta="50"/> + <has_image_height height="3000" delta="50"/> <has_image_width width="3192" delta="50"/> </assert_contents> </element> - <element name="job.predicted_labels_concordance_OS_STATUS"> - <assert_contents> - <has_image_channels channels="3"/> - <has_image_height height="2558" delta="50"/> - <has_image_width width="2794" delta="50"/> - </assert_contents> - </element> </output_collection> </test> <!-- test 15: pr curve plot --> <test expect_num_outputs="2"> - <expand macro="common_test"> + <expand macro="common_test_class"> <section name="plot"> <conditional name="plot_pr_curves_conditional"> <param name="plot_pr_curves" value="yes"/> @@ -1243,7 +1228,7 @@ </section> </expand> <output_collection name="plots" type="list"> - <element name="job.predicted_labels_pr_curves_OS_STATUS"> + <element name="job.predicted_labels_pr_curves_class"> <assert_contents> <has_image_center_of_mass center_of_mass="975,732" eps="20"/> <has_image_channels channels="3"/> @@ -1255,7 +1240,7 @@ </test> <!-- test 16: roc curve plot --> <test expect_num_outputs="2"> - <expand macro="common_test"> + <expand macro="common_test_class"> <section name="plot"> <conditional name="plot_roc_curves_conditional"> <param name="plot_roc_curves" value="yes"/> @@ -1265,7 +1250,7 @@ </section> </expand> <output_collection name="plots" type="list"> - <element name="job.predicted_labels_roc_curves_OS_STATUS"> + <element name="job.predicted_labels_roc_curves_class"> <assert_contents> <has_image_center_of_mass center_of_mass="970,730" eps="20"/> <has_image_channels channels="3"/> @@ -1277,7 +1262,7 @@ </test> <!-- test 17: boxplot plot --> <test expect_num_outputs="2"> - <expand macro="common_test"> + <expand macro="common_test_class"> <section name="plot"> <conditional name="plot_boxplot_conditional"> <param name="plot_boxplot" value="yes"/> @@ -1287,7 +1272,7 @@ </section> </expand> <output_collection name="plots" type="list"> - <element name="job.predicted_labels_box_plot_OS_STATUS_0_LIVING"> + <element name="job.predicted_labels_box_plot_class_buz"> <assert_contents> <has_image_center_of_mass center_of_mass="1485,882" eps="20"/> <has_image_channels channels="3"/> @@ -1295,7 +1280,7 @@ <has_image_width width="2967" delta="20"/> </assert_contents> </element> - <element name="job.predicted_labels_box_plot_OS_STATUS_1_DECEASED"> + <element name="job.predicted_labels_box_plot_class_qux"> <assert_contents> <has_image_center_of_mass center_of_mass="1485,882" eps="20"/> <has_image_channels channels="3"/> @@ -1312,9 +1297,8 @@ <conditional name="plot_cox_conditional"> <param name="plot_cox" value="yes"/> <param name="omics_name" value="bar"/> - <param name="clinical_variables" value="Crizotinib, Erlotinib"/> + <param name="clinical_variables" value="2,3"/> <param name="top_features" value="10"/> - <param name="event_value" value="1:DECEASED"/> <conditional name="crossval_conditional"> <param name="crossval" value="yes"/> <param name="n_splits" value="5"/> @@ -1325,7 +1309,7 @@ </section> </expand> <output_collection name="plots" type="list"> - <element name="job.final_model_cox_hazard_ratios"> + <element name="job.feature_importance.IntegratedGradients_cox_hazard_ratios"> <assert_contents> <has_image_center_of_mass center_of_mass="972,737" eps="20"/> <has_image_channels channels="3"/> @@ -1353,12 +1337,7 @@ <conditional name="model_class"> <param name="model_class" value="DirectPred"/> </conditional> - <repeat name="targets"> - <param name="target_variables" value="3"/> - </repeat> - <repeat name="targets"> - <param name="target_variables" value="2"/> - </repeat> + <param name="target_variables" value="3,2"/> <section name="advanced"> <param name="hpo_iter" value="1"/> </section> @@ -1400,7 +1379,7 @@ <has_n_lines n="25"/> </assert_contents> </element> - <element name="job.feature_logs.omics_foo"> + <element name="job.feature_logs.foo"> <assert_contents> <has_n_lines n="25"/> </assert_contents>